The present invention relates to automating location of expertise, and more specifically, to using associations between individuals and specific objects (which inherit from classes in a hierarchy) to find experts about a particular subject area, and in response to a search of a more general superclass, finding experts associated with particular objects inheriting from that superclass.
Expertise location is the process of identifying individuals with the relevant knowledge or skills to solve a problem. Some existing expertise location systems merely provide a directory of people and their topics of expertise. These systems can be queried to find people asserted to be experts on a topic, or the list of topics that a person is considered an expert on. Such systems have a variety of drawbacks:
1. The possible expertise topics may be fixed. This prevents an expert from asserting their expertise in an area not thought of by the designers of the expertise location system.
2. The possible expertise topics may be open-ended, such as keywords or search terms. It is time-consuming and very difficult for an expert to think of the keywords that an expertise seeker may try.
3. The possible expertise topics may be unstructured. The expert may have the burden of asserting topics at many levels of specificity for the same general area of expertise.
4. It may be labor-intensive for an expert to keep manually associated topics of expertise up-to-date as their skills or knowledge change.
Some expertise location systems analyze knowledge artifacts such as bookmarks or written documents to automatically determine relevant expertise, typically associating users with particular keywords. Although this removes the need for explicit expert/topic association, it can be difficult to correct mistaken associations or for a user to judge the amount or scope of another's expertise.
Some expertise location systems, such as IBM's BlueReach, maintain a taxonomy of expertise topics. This avoids having to think of specific keywords to use as expertise topics, and may allow the expert to assert expertise on a family of related concepts, but such systems typically do not allow easy modification of the possible expertise topics by end users.
Some expertise location systems, such as IBM's SmallBlue, take advantage of contextual information such as the seeker's social network to improve the ranking of suggested experts, i.e. ranking more highly those experts that a seeker knows or can ask for an introduction to. Although this is useful information for the expertise seeker, it is primarily helpful when there is an abundance of experts, or where the seeker is comfortable asking for personal referrals.
Applicants have discovered that in order to solve these problems, an expertise location system must have the following properties:
1. The possible expertise topics must be extensible.
2. Experts should be guided towards reusing common terms, rather than an open-ended variety of terms that describe the same topic.
3. The topics should be arranged in a hierarchy that allows easy expert association with either a very specific topic or a more general area of expertise.
4. The expertise location should take implicit expertise as well as explicitly asserted expertise into account. Ideally, at least one expert should be locatable for every topic.
5. In addition to locating experts by topic, the architecture should support enumerating the topics that a particular individual is an expert on. The full set of expertise should be filterable to only the subset that is relevant to a given context.
6. The system must be able to provide the list of experts for a provided topic in a sorted order, beginning with the experts who have the most relevant expertise.
7. The system must be able to provide some explanation of why a particular person was recommended as an expert on a provided topic.
8. To make efficient use of computational resources, the expertise location algorithm should support a configurable target count of experts. In some cases, one may only need to know if a topic has any associated expert or not. In other cases, one may need an exhaustive list of associated experts.